Propsight Startup Playbook

Our central guide for strategy, operations, and culture. Version 1.0

I. Core Company Information

Our Reason for Building This

We founded Propsight because we’ve lived the pain of making real estate decisions without clarity. The tools available today are fragmented, rigid, and data-poor. Whether you're a buyer trying to understand why homes in a neighborhood keep turning over, or an investor hunting for unseen value, the process feels like crawling through mud. Propsight isn’t just another app. It’s the foundation of a new way of thinking, searching, and deciding in real estate.

Who We Are

Propsight is an AI-native PropTech startup focused on humanizing real estate intelligence. We believe data should be interpreted, not dumped. Filters should become conversations. Images should be understood, not just shown. And insights should feel like they come from a real, trusted expert.

Our Secret Sauce – Agent-as-a-Service (AaaS)

At the core of our technology is a deeply integrated Agent-as-a-Service (AaaS) architecture—a real estate-savvy, AI-driven backend that behaves like a full-stack digital agent. It brings together natural language understanding, multimodal interpretation (images, text, geodata), vector-based search, and real estate heuristics. This is not just an assistant—it’s the operating core that powers every module.

Business Strategy

  • Go-to-Market: A "land-and-expand" model. Launch public-facing MVPs (GeoGuard, PromptLens) to gather traffic and validate assumptions before pursuing full MLS access and paid products.
  • Target Market: Initial focus on data-savvy investors and tech-forward agents, then expand to the broader market of renters, buyers, and brokerages.
  • Competitive Positioning: We are not a listings portal; we are an intelligence layer. Our AaaS core provides conversational, multi-dimensional analysis that traditional platforms cannot replicate.

II. Key Business Processes

Sales and Marketing

  • Customer Acquisition: Lightweight marketing tests (landing pages, community content), SEO based on data insights, and direct outreach to early adopters and potential API partners.
  • Sales Process: Product-led growth driven by the utility of our free tools, converting to paid tiers (Modular SaaS, API access) as users see value. Future direct sales for white-labeling and enterprise data.

Product Development

  • Lifecycle: Agile sprints focused on rapid MVP deployment, user feedback collection, and continuous iteration.
  • Roadmap:
    • **Pre-Investment:** Launch MVPs (GeoGuard, PromptLens, RepairWise Lite).
    • **Post-Investment:** Secure MLS access, launch full product suite, and begin scaling user base and revenue streams according to our 5-year plan.

Monetization Strategy

  • Modular SaaS: Pricing by feature (e.g., GeoGuard for agents, RepairWise for investors).
  • API Access: Tiers for developers and other SaaS platforms.
  • White-labeled Tools: Dashboards for brokerages and agencies.
  • Insight-as-a-Service: Enriched data for institutional buyers (hedge funds, REITs).

III. Essential Resources & Tools

  • Proprietary AaaS Core: Our central intellectual property.
  • Technical Team: Experts in AI, cloud computing, and real estate data.
  • Data Sources: A mix of public data (FEMA, census, satellite) and licensed data (MLS, tax records).
  • AI/ML Stack: Python, TensorFlow/PyTorch, vector databases (e.g., Pinecone), and LLM APIs.
  • Cloud Provider: AWS, Google Cloud, or Microsoft Azure.

IV. Key Performance Indicators (KPIs)

  • Pre-Investment: User engagement on MVPs (prompts used, reports generated), landing page conversion rates, email list growth.
  • Post-Investment: Monthly Active Users (MAU), Customer Acquisition Cost (CAC), Free-to-Paid Conversion Rate, API call volume, Annual Recurring Revenue (ARR).

V. Important Considerations & Known Risks

Risks & Constraints

  • MLS Access: Can be regional, slow to negotiate, and restrictive.
  • Legal Compliance: Licensing of images and adherence to fair housing laws are critical.
  • Data Cost & Scale: Some datasets are not public and can be expensive.

Strategic Response

  • Focus on public-data-first tools (GeoGuard, PromptLens) to build initial traction.
  • Use crawled sample data for demos before full listing access is secured.
  • Show utility without full MLS integration to gain leverage in negotiations.